Target detection method based on dynamic programming

Abstract

The invention discloses a target detection method based on dynamic programming. The target detection method mainly resolves the problems that in the prior art, target detection performance is influenced due to the facts that too many false points of a target are detected in a high-noise environment or a strong-clutter environment and a phenomenon of frame loss exists. The target detection method comprises the steps that 1) pulse pressure and moving target detection are carried out on received data; 2) low threshold transverse false-alarm detection is carried out on data after the moving target detection, and points exceeding a threshold are marked to be of normal states; 3) cost values of all the normal states and relation states in continuous five frames are calculated; 4) relation states with small cost values are searched for reversely; 5) summation of amplitudes of the relation states of a searching path is carried out, and threshold detection is carried out, so a target detection result is obtained. According to the target detection method, a state transition cost function determined by the distance and speed is constructed, the characteristic that the relation cost value between two target frames is small is utilized, most of strong clutter points and noise points are filtered out, precision for target detection in the high-noise environment or the strong-clutter environment is improved, and the target detection method can be used for target tracking of a low altitude warning radar.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a target detection method, which can be used to detect slow small targets under the background of weak signals or strong clutter. technical background [0002] With the continuous development of modern technology and the emergence of some artificial interference or new electronic products, the combat environment of radar is becoming more and more complex, and the target signal is easily submerged in noise and clutter. The detection of slow and small targets is one of the problems that modern radars need to solve urgently. [0003] In radar signal processing, TBD, a technology called tracking first and detection later, which has appeared in recent years, can make full use of the information in each stage of the processing process, improve the detection performance of small targets, and realize the detection of small targets in harsh environments. . ...

AI Technical Summary

Problems solved by technology

[0004] In the article "An Effective Algorithm for Radar Weak Target Detection, Acta Electronics, No. 3, 2003", Qiang Yong and others proposed the idea of ​​joint detection of constant false alarm CFAR and tracking before detection TBD, that is, adding The low-threshold CFAR detection and ranking process preprocesses the data and introduces the concept of smoothness to eliminate some false tracks. Although the detection performance and calculation amount are improved to a certain extent, the tracking effect of this method is poor

[0005] In the article "A Dynamic Programming TBD Algorithm Based on Target State Correlation, Journal of Air Force Radar Academy, No. 6, 2011", Wu Weihua and others proposed a dynamic programming TBD algorithm based on target state correlation. Motion characteristics and the use of multi-frame data to reduce amplitude fluctuations, although the impact of noise is reduced, compared with traditional methods, the detection performance is improved, but if a certain frame of the target is lost during the detection process, the tracking performance will be greatly reduced

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